数字经济赋能中国制造业全要素生产率的效应测度及路径分析

杜传忠¹　刘书彤²

（1. 南开大学经济与社会发展研究院；2. 南开大学经济学院）

　　内容提要：推进数字经济与制造业深度融合、提升数字经济赋能制造业全要素生产率，已成为推动中国制造业高质量发展的重要路径。本文利用2003—2020年中国制造业省级面板数据，通过构建随机前沿全赋能效应模型，运用反事实分析方法，分析数字经济对中国制造业全要素生产率的赋能效应及作用路径。研究结果表明：数字经济对制造业全要素生产率具有明显的赋能效应，这种效应主要通过技术进步、技术效率和规模效率三条路径实现，其中，通过技术进步赋能制造业全要素生产率为主要作用路径。异质性检验结果表明，在合理化、高级化程度较低的地区，数字经济对制造业全要素生产率的赋能效应较大，而赋能技术效率的效应相对较小；在市场化水平较高的地区，数字经济与制造业深度融合，着力发挥数字经济对技术进步赋能作用，使得数字经济深度赋能制造业全要素生产率的效果更为明显；数字经济对南方地区制造业全要素生产率的赋能效应更为显著。为进一步提升数字经济赋能中国制造业全要素生产率，促进制造业高质量发展，应大力推进数字经济与制造业融合。

　　

　　关键词：数字经济；制造业；全要素生产率；区域差异；随机前沿模型

　　

　　作者简介：杜传忠，南开大学经济与社会发展研究院教授、博士生导师，天津，300071；刘书彤，南开大学经济学院博士研究生，通信作者。

　　基金项目：国家社会科学基金重大项目“新一代人工智能对中国经济高质量发展的影响、趋向及应对战略研究”（20&ZD067）；国家社会科学基金重点项目“工业化后期与新产业革命交汇下的中国制造业与服务业融合发展研究”（19AJY012）

　　引用格式：杜传忠,刘书彤.数字经济赋能中国制造业全要素生产率的效应测度及路径分析[J].经济与管理研究,2023,44(9):43-65.DOI:10.13502/j.cnki.issn1000-7636.2023.09.003.

　　

　　

Effect Measurement and Path Analysis of Total Factor Productivity in China’s Manufacturing Industry Empowered by the Digital Economy

DU Chuanzhong, LIU Shutong

(Nankai University, Tianjin 300071)

　　

　　Abstract: Promoting the deep integration of the digital economy and the manufacturing industry and improving total factor productivity (TFP) of the manufacturing industry empowered by the digital economy becomes an important path to enhance the high-quality development of China’s manufacturing industry. By theoretically revealing the mechanism of the digital economy empowering manufacturing TFP, this paper uses the provincial panel data of China’s manufacturing industry from 2003 to 2020 to introduce the digital economy into a stochastic frontier model. Based on the counterfactual analysis method, this paper empirically tests the empowering effect of the digital economy on manufacturing TFP, and investigates the action paths of technical efficiency, technological progress, and scale efficiency. It further analyzes the heterogeneity of the digital economy on manufacturing TFP at different levels, including industrial structure, marketization level, and regional level.

　　The results indicate that the digital economy has an obvious empowering effect on manufacturing TFP, with technological progress playing a dominant role. The heterogeneity test shows that the digital economy has a greater empowering effect on manufacturing TFP in regions with low levels of rationalization and upgrading of industrial structure. However, this effect on empowering technical efficiency is relatively small. Meanwhile, in regions with high levels of marketization, the deep integration of the digital economy and the manufacturing industry can effectively enhance manufacturing TFP by fully leveraging the role of the digital economy in technological progress. Furthermore, the empowering effect of the digital economy on manufacturing TFP is more significant in southern regions than in northern regions.

　　The marginal contributions of this paper are as follows. First, based on the decomposition theory of TFP, the digital economy is included in the growth accounting framework and the TFP measurement framework. Second, the stochastic frontier models of technical efficiency, technological progress, production factors, and the full empowering effect are constructed to accurately measure the empowering effect of the digital economy on manufacturing TFP. Third, the counterfactual analysis method is used to effectively peel off the empowering effect of the digital economy. Finally, it demonstrates the dynamic process of the full empowering effect of the digital economy on manufacturing TFP.

　　Based on the findings, this paper provides corresponding policy insights for further improving the digital economy to empower China’s manufacturing TFP and promoting high-quality development of the manufacturing industry, including promoting the digital and intelligent transformation of the manufacturing industry, giving full play to the empowering effect of the digital economy on manufacturing scale efficiency, technological progress, and technical efficiency, and implementing differentiated development strategies for the manufacturing industry.

　　Keywords:  digital economy; manufacturing industry; total factor productivity; regional difference; stochastic frontier model